Agreement between participant-rated and compendium-coded intensity of daily activities in a triethnic sample of women ages 40 years ears and older

Agreement Between Participant-Rated and Compendium-Coded Intensity of Daily Activitiesin a Triethnic Sample of Women Ages 40 Years and Older

Sara WilcoxDepartment of Exercise Science

Norman J. Arnold School of Public Health, University of South Carolina

Melinda L. IrwinFred Hutchinson Cancer Research Center

Cheryl AddyDepartment of Epidemiology and Biostatistics


Barbara E. AinsworthDepartment of Exercise Science, Department of Epidemiology and Biostatistics, and Prevention Research Center


Lisa StolarczykCenter for Exercise and Applied Human Physiology

University of New Mexico

Melicia WhittCenter for Clinical Epidemiology and Biostatistics

University of Pennsylvania School of Medicine

Catrine Tudor-LockePrevention Research Center


ABSTRACT

Participant-rated and compendium-coded intensity of dailyphysical activities were compared in 148 African American, 144Native American, 51 non-Hispanic White women ages 40 to 91years who completed 4 days of activity records. For compen-dium-coded intensity, reported activities were classified as light(< 3 metabolic equivalents [METS]), moderate (3–6 METS), orvigorous (> 6 METS) using the Compendium of Physical Activ-ities (1), whereas these categories were self-assigned for partic-ipant-rated intensity. Minutes per day (min/d) spent in activitiesat each intensity level were computed. Relative to compen-dium-coded min/d, participants reported significantly greater

time spent in light (+10 min/d; p < .01) and vigorous (+17min/d; p < .001) activities, and less time spent in moderate ac-tivities (–27 min/d; p < .001). Similarly, compendium-coded es-timates yielded higher rates of participants meeting Centers forDisease Control and Prevention–American College of SportsMedicine and Surgeon General recommendations than partici-pant-rated estimates (11–18% differences) but substantiallylower rates meeting American College of Sports Medicine vig-orous recommendations (22% difference). Further, 247 greaterkilocalories per day were estimated based on compen-dium-coded intensity. Kilocalories per day estimates based oncompendium codings were more highly associated with pedom-eter counts than those based on participant ratings (p < .05).Study patterns were generally seen across all sample subgroups.Discrepancies between participant and compendium estimatesare likely to be most meaningful in studies estimating energy ex-penditure as it relates to health outcomes and in studies estimat-ing vigorous activities.

(Ann Behav Med 2001, 23(4):253–262)

INTRODUCTION

Women of color experience disproportionate rates ofchronic disease, with coronary heart disease, diabetes, and sometypes of cancers more prevalent in African American and NativeAmerican than White women (2). Regular participation in mod-erate-intensity physical activity (PA) is associated with a host ofphysical and psychological health benefits, including a reducedrisk of coronary heart disease, diabetes, colon cancer, and obe-

253

This study was supported by a grant awarded to Dr. Barbara E.Ainsworth, National Institutes of Health (NIH) WHI SIP#22W–U48/CCU409664.

We thank Loretta Finnegan, MD, from the NIH Women’s Health Initia-tive, and Pat Riley, CNM, MPH from the Centers for Disease Control andPrevention Research Centers for their support. We recognize VivianHeyward, Rob Robergs, Julia Orri, Farzareh Ghiasvand, Ann Gibson,and Donna Lockner from the University of New Mexico and AngelaMorgan, Jennifer Hootman, Katrina Drowatzky, Rod Velliquette, PaulDavis, Ming Zhao, Sarah Levin, and Dawn Tittsworth from the Univer-sity of South Carolina for their contributions in this study.

Reprint Address: S. Wilcox, Ph.D., Department of Exercise Science,Norman J. Arnold School of Public Health, University of SouthCarolina, Columbia, SC 29208. E-mail: [email protected]

© 2001 by The Society of Behavioral Medicine.

sity, and enhanced mood and quality of life (3). Yet, nationalsurveys indicate that the majority of U.S. adults are not active atthe level needed to attain these benefits. Women, particularlyolder and ethnic minority women, consistently have lower ratesof participation in PA than men, as assessed by traditional mea-sures (4). Recent reports, however, suggest that traditional PAmeasures may not assess activities that are more common in thelives of women, including child care and housework (5). As a re-sult, there has been a call to develop and validate PA assessmentmeasures that are more gender and ethnically relevant (5,6).

PA surveys often require the respondent to estimate the in-tensity level of their reported activities, with intensity codes as-signed from predetermined lists. In addition, they often requirerespondents to recall the number of minutes spent in activities ofvarying intensities. Cultural factors likely impact the experienceand reporting of PA (7,8). For example, cultural beliefs influ-ence the value placed on PA versus rest (9), the experience ofstressful or unpleasant activities as being of high intensity (6),the relative importance of different barriers and incentives to PA(9–11), and the types of physical activities participated in, withhousehold and caregiving activities more common than sport orexercise in women (5,6,12). It is not clear how well perceived in-tensity levels correspond with more standardized coding sys-tems that are commonly used in research (e.g., Compendium ofPhysical Activities [1]) among women in general, and ethnicminority women in particular. The current public health empha-sis on moderate-intensity PAs underscores the importance ofbetter understanding women’s perceptions of PA intensity.

Other factors that may impact the experience and reportingof PA include body mass or overweight status, age, education,and response set biases. Although a higher body mass index(BMI) has been associated with underreporting of time spent inaerobic activities (13), other studies have shown that obese indi-viduals overestimate the duration of moderate to higher intensityactivities (14), the total minutes of exercise performed (15), andtotal energy expended (16). In terms of age, Wilcox and King (17)found that older age was associated with overestimating activitylevel relative to peers, but Blair et al. (18) found that age was unre-lated to the accuracy of retrospective recalls of PA. Level of edu-cation has not been examined in relation to PA bias. Finally, socialdesirability (19) and self-favoring bias theories (20,21) describethe tendency of individuals to present themselves in an overlypositive or culturally appropriate light for self-esteem enhance-ment, which may lead to overestimates of PA.

The purpose of this study was to compare participant-ratedwith compendium-coded (1) intensity of time spent in daily ac-tivities, PA classification, and daily kilocalories expendedamong African American, Native American, and non-HispanicWhite middle-aged women. Although we do not argue that onemethod is more “accurate” than the other, discrepancies be-tween measures indicate the presence of measurement error andcan lead to different interpretations regarding energy expendi-ture and PA classification, as well as different predictions re-garding health outcomes. This study also examined whetheragreement between methods varied as a function of ethnicity,age, education, and BMI.

METHOD

Participants

This study is a part of The Cross-Cultural Activity Partici-pation Study, a 5-year community study affiliated with theWomen’s Health Initiative community studies (5). Participantsincluded 168 African American women residing in SouthCarolina, 156 Native American women residing in Pueblo andNavajo reservations in New Mexico, and 53 White women re-siding in South Carolina (n = 28) and New Mexico (n = 25). Par-ticipants were recruited through advertisements placed in news-letters, fliers posted in community centers, radioadvertisements, and personal conversations. Prior to study en-rollment, participants were screened during a telephone call forinclusion criteria of (a) 40 years of age or older; (b) self-identi-fied ethnicity as African American, non-Hispanic White, or atleast 50% Native American; (c) absence of physical illnesses ordisabilities that would limit daily physical activities such aswalking; and (d) the ability to read and write in English wellenough to record daily physical activities in a record book.

Participants gave written informed consent for participationin research as approved by the University of South Carolina’sand the University of New Mexico’s Institutional Review Board.Participants were given $25 for successful completion of thetwo visits. Among the 377 women enrolled in the study, 16 with-drew due to time demands, 5 had health problems that limitedtheir study activities, 11 were noncompliant with the study pro-tocol, and 2 had incomplete data on the PA records. After ex-cluding these 34 participants, data from 343 women were avail-able for these analyses.

Procedures

Data for this study involved two visits completed at the par-ticipants’ homes or worksites or at the study center. Data collec-tion and testing procedures were standardized through prelimi-nary training sessions of all field and laboratory staff. The samestudy procedures and models of laboratory equipment wereused at each site to obtain study data. All data were entered andanalyzed at the University of South Carolina.

Measures

Sociodemographics. Interviewer-administered surveys de-signed to obtain demographic and health behavior informationwere administered to each participant. Ethnicity was obtainedfrom the demographic survey and reported as African Ameri-can, non-Hispanic White, or at least 50% Native American.

PA. PA Records were used to obtain a detailed account of allPA performed during one consecutive 4-day period. Prior tostarting the PA recording, participants were given detailed in-structions in the use of the PA Records. PA recordings beganwhen participants awoke in the morning until they went to bed inthe evening. For each new activity, participants recorded thetime they began the activity, a description of the activity, theirbody position while doing the activity (reclining, sitting, stand-

254 Wilcox et al. Annals of Behavioral Medicine

ing, or walking), their perceived effort while doing the activity(light, moderate, or vigorous), and a category for the activity(e.g., self-care, household, parenting, transportation, occupa-tion, walking, inactivity, lawn and garden, exercise and condi-tioning, and miscellaneous). A sample PA Record is shown inTable 1. Categories were obtained from the 1993 Compendiumof Physical Activities (1). Participants were instructed to thinkof intensity in terms of “physical effort” rather than “mental ef-fort.” For example, driving in traffic might be “mentally vigor-ous” but not “physically vigorous” because the person is sittingin a car. Within 2 days of completing the PA Records, twotrained study staff edited the PA Records for accuracy and clar-ity in the presence of the study participants. General principlesfor editing the PA Record were to make sure participants (a) re-corded a start and stop time for each activity, (b) recorded all ac-tivities from when they awoke in the morning until they went tobed in the evening, (c) circled a body position for each activity inthe PA Record, (d) circled a perceived effort for each activity inthe PA Record, and (e) circled an activity category for each ac-tivity in the PA Record.

PA Records were coded for data entry and analyses usingmethods outlined in the Compendium of Physical Activities (1).Two trained study staff coded each PA Record independently.Differences in assigned compendium codes between the study

staff were adjudicated by a third reviewer. A stratified (by staffmember, with those staff members who coded more PA Recordsselected more often) random sample of 24 PA Records was se-lected to assess interrater reliability. Agreement between raterswas 95% in instances where both persons provided a code. Ap-proximately 2.5% of the data were coded by one person and notcoded by the other. The metabolic equivalent (MET) intensityreflects the associated metabolic rate for a specific activity di-vided by a standard resting metabolic rate. Individual differ-ences that may alter the energy cost of movement (e.g., bodymass) are not taken into account. Therefore, compen-dium-coded PA was described in terms of absolute intensity.

PA Record data were double-entered into a computer usingthe Epi-Info data entry and statistical program. PA data weresummed as minutes per day (min/d) spent in activities (as re-ported by the participant) by the MET intensity level (compen-dium-coded) and by the participant ratings (participant-rated).Thus, only the ratings of intensity differed for participant-ratedand compendium-coded activities. The duration of activitieswas equal to the participant-reported minutes for both measures.For compendium-coded values, minutes per day were sortedinto intensity groups using the Centers for Disease Control andPrevention–American College of Sports Medicine(CDC–ACSM) recommendations for light (< 3 METs), moder-ate (3–6 METs), and vigorous (> 6 METs) intensity activities(22). Minutes per day in light, moderate, and vigorous activitiesrepresent the average minutes per day over the 4-day period inwhich PA Records were kept.

Estimates of energy expenditure. For participant-rated andcompendium-coded activity, we also computed an estimate ofkilocalories expended per day (kcal/d). We summed theMET-minutes (number of minutes multiplied by MET assign-ment) for all activities, multiplied these MET-minutes by theparticipant’s weight in kilograms, and divided by 60 min (1). Tocompute the kilocalories per day estimate for participant-ratedactivities, we used MET values of 1.25 for light activities (com-bines light activities and sleeping), 4 for moderate activities, and7 for vigorous activities. These values correspond to those usedin the Seven Day PA Recall (23), a well validated interview-ad-ministered survey of PA. To compute the kilocalories per day es-timate for compendium-coded activities, we used the MET val-ues specified in the Compendium of Physical Activities (1).

Percentage meeting PA recommendations. We computedthe percentage of participants who met CDC–ACSM (22) rec-ommendations for moderate-intensity PA (≥ 30 min of moder-ate-intensity activities each of the 4 days), Surgeon General rec-ommendations (3) for PA (≥ 150 kcal/day expended in at leastmoderate-intensity activities for each of the 4 days), and ACSMcriteria (24) for vigorous PA (≥ 20 min, ≥ 2 of the 4 days as-sessed) based on our two methods (participant-rated vs. com-pendium-coded).

Pedometer counts of activity. Women wore a YamaxDigiwalker for the 4-day period. Although pedometers such as

Volume 23, Number 4, 2001 Agreement in Activity Intensity 255

TABLE 1Example of a Physical Activity Record

TimeBegan Position

Description (WhatAre You Doing?)

HowHard?

ActivityGroup

7:15 Recline Dressing Light SC HH PARSit Moderate TRANS OCCStand Vigorous WALK INACWalk LG EC MISC

7:25 Recline Walking in the house Light SC HH PARSit Moderate TRANS OCCStand Vigorous WALK INACWalk LG EC MISC

7:30 Recline Walking for exercise Light SC HH PARSit Moderate TRANS OCCStand Vigorous WALK INACWalk LG EC MISC

8:00 Recline Watching TV news Light SC HH PARSit Moderate TRANS OCCStand Vigorous WALK INACWalk LG EC MISC

8:10 Recline Cooking breakfast Light SC HH PARSit Moderate TRANS OCCStand Vigorous WALK INACWalk LG EC MISC

Note. For demonstration purposes of the physical activity record, sectionsto be circled were completed in boldface. In practice, the respondent wouldcircle the body position, perceived effort, and the physical activity group andwrite the time that he or she began a new activity and specific type of activityperformed. SC = self care; HH = household; PAR = parenting; TRANS =transportation; OCC = occupation; WALK = walking; INAC = inactivity; LG =lawn and garden; EC = exercise/conditioning; MISC = miscellaneous.

this one do not directly assess intensity of activity, they do pro-vide an indication of total steps taken throughout one’s day, andthey are most accurate when walking (as opposed to cycling,swimming, etc.) is a person’s predominant form of activity (25).Every night before retiring to bed, women recorded the numberof steps measured by the pedometer, and the number of stepswere averaged over the 4 days. These data provide an alternativeto self-report measures of PA.

Obesity. Obesity status was expressed using BMI computedas weight in kilograms divided by height (without shoes) insquare meters. Body weight was measured to the nearest 0.1 kgusing a Seca Model 770 scale (Shorr Productions, Olney, MD).Height was measured to the nearest 0.1 in. using a stadiometerand converted to meters. Obesity was defined as a BMI greaterthan or equal to 30 kg/m2 (26).

Statistical Analyses

Descriptive statistics for the sample were conducted sepa-rately for each ethnic group. Average participant-rated and com-pendium-coded minutes per day spent in light, moderate, andvigorous intensity activities from the 4-day PA Records andkilocalories per day are reported for the overall sample. To testwhether agreement varied as a function of ethnicity (AfricanAmerican, Native American, non-Hispanic White), age (< 60years, ≥ 60 years), education (< 12 years, ≥ 12 years), and obe-sity status (BMI < 30 kg/m2, BMI ≥ 30 kg/m2), means and stan-dard deviations were computed separately for each subgroup. Ttests were conducted to examine whether the differences be-tween participant-rated and compendium-coded minutes per

day for each intensity level and for kilocalories per day were sig-nificantly different from zero. In addition, differences in ratingsbetween ethnic groups were tested with an analysis of variance(ANOVA) followed with Tukey’s Honestly Significant Differ-ence test for pairwise differences. Differences in rating betweendifferent age, education, and obesity status groups were testedwith independent sample t tests (age, education, and obesity sta-tus). Correlations between participant-rated and compen-dium-coded estimates were also computed for minutes per dayof light, moderate, and vigorous intensity.

Differences in the percentage meeting CDC–ACSM, Sur-geon General, and ACSM vigorous recommendations for PAusing compendium-coded and participant-rated estimateswere also examined for the overall sample and by the varioussample strata. Differences were tested with chi-square statis-tics. In instances where the sample size in one or more cellswas less than 5, the Fisher’s Exact Test was computed (andonly p values are reported).

Finally, we computed the correlations between pedometercounts and average kilocalories per day (for participant-ratedand compendium-coded estimates) for each ethnic, age, educa-tion, and obesity status group. All correlations were adjusted forage, weight, education, and race. The difference in correlationswere examined with t tests for dependent correlations (27).

RESULTS

Sample Characteristics

Characteristics of the sample are shown in Table 2. Al-though the overall ANOVA indicated a significant relation be-


TABLE 2Characteristics of the Sample by Ethnic Group

Ethnic Group

Characteristic African American Native American Non-Hispanic White F

n 148 144 51Age (years)

M (SD) 55.4 (10.8) 52.4 (10.8) 55.5 (11.3) 3.3*Range 40–82 40–91 40–81≥ 60 years (%) 37.2 19.43 5.3

Education (years)M (SD) 14.6 (3.1) 14.0 (2.7) 16.1 (2.7) 9.5***Range 7–20 4–20 9–20< 12 years (%) 12.2 7.6 2.0

Weight (kg)M (SD) 81.5 (18.5) 73.2 (16.1) 68.23 (13.8) 15.1***Range 46.4–154.0 41.9–127.9 49.3–127.6

Height (cm)M (SD) 164.1 (5.8) 156.6 (6.0) 164.9 (5.9) 72.6***Range 151.1–180.0 142.0–169.8 153.7–178.0

Body mass index (kg/m2)M (SD) 30.3 (6.8) 29.8 (6.2) 25.1 (4.7) 14.0***Range 17.8–55.4 17.9–52.0 18.1–.43.7≥ 30 kg/m2 (%) 45.9 42.4 11.8

Note. N = 343.*p < .05. **p < .01. ***p < .001.

tween race and age, no pairwise differences between the threeethnic groups were statistically significant. Non-HispanicWhite women reported significantly greater years of formal ed-ucation than African American and Native American women.Consistent with population data (28), non-Hispanic Whitewomen also had a significantly lower BMI than African Ameri-can and Native American women. African American womenweighed significantly more than Native American and non-His-panic White women. Finally, Native American women were ofshorter stature than either African American or non-HispanicWhite women.

Participant-Rated Versus Compendium-CodedMinutes per Day Spent in Light, Moderate, andVigorous Intensity Activities

In the overall sample, participants reported that they spent1,340 min/d in light, 79 min/d in moderate, and 21 min/d in vig-orous activities. Applying MET values from the Compendiumof Physical Activities (1) to the participants’ reported activitiesand duration of activities yielded compendium-coded estimatesof 1,330, 106, and 4 min/d spent in light, moderate, and vigorousactivities, respectively. Thus, relative to compendium-coded es-timates, participants reported more minutes per day spent inlight activities (difference = 9.5 min/d) t(342) = 2.5, p < .01, andvigorous activities (difference = 17.3 min/d), t(342) = 8.8, p <.001, and fewer minutes per day in moderate activities (differ-ence = –26.7 min/d), t(342) = –7.1, p < .001. These values corre-spond to effect size estimates of d = .12 (small), d = .38 (small tomedium), and d = .63 (medium to large) for light, moderate, andvigorous minutes per day, respectively (29).

As shown in Table 3, Native American, non-HispanicWhite, middle-aged, more educated, and nonobese women re-ported significantly more time spent in light activities relative tocompendium-coded estimates. In contrast, participant-ratedtime spent in moderate intensity activities was less and timespent in vigorous intensity activities was greater than compen-dium-coded estimates for women in all subgroups (women withless than a high school education, p < .06).

Differences in participant-rated versus compendium-codedminutes of PA were found between ethnic groups for light activ-ity, F(2, 340) = 4.52, p < .02, and moderate activity, F(2, 340) =5.94, p < .01. African American women had a significantlylower difference score than non-Hispanic White women forlight activity, and a significantly lower difference score thanboth non-Hispanic White and Native American women formoderate activity. There were no ethnic group effects for vigor-ous activity difference scores, F(2, 340) = 0.69, p > .40. In addi-tion, there was not a significant difference in participant-ratedversus compendium-coded minutes per day between age, edu-cation, or obesity status groups for any intensity level.

Finally, correlations between compendium-coded esti-mates and participant-rated estimates of minutes of PA per daywere .60 for light intensity, .50 for moderate intensity, and .23for vigorous intensity, p < .001. Although correlations were sim-ilar across the sample subgroups for light and moderate intensity(r = .37–.65), they varied for vigorous intensity, with higher and

statistically significant (p < .001) correlations observed for Afri-can Americans (r = .45), those younger than 60 years (r = .30),those who were not obese (r = .32), and those with more educa-tion (r = .25). Vigorous-intensity correlations were low and notsignificant for Native Americans (r = .14), Whites (r = .04),older women (r = –.06), obese women (r = .00), and those withless education (r = –.12).

Estimates of Kilocalories per DayUsing Participant-Rated VersusCompendium-Coded Intensity

As shown in Table 4, the kilocalorie per day estimates forparticipant-rated (2,707) and compendium-coded estimates(2,954) differed by 247 kcal/day, t = –12.7, p < .001. This patternof higher estimates for compendium-rated estimates was truefor all sample strata. The difference between kilocalorie per dayestimates based on participant-rated versus compendium-codedestimates did not vary by race, age, education, or obesity status.

Correlations Between Kilocalories per Dayand Pedometer Counts

Also shown in Table 3, the correlation between kilocaloriesper day and pedometer counts was significantly greater whencompendium estimates of MET values were used as comparedto participant estimates of intensity (r = .28 and .17, respec-tively), t(306) = –2.0, p < .05. Significant differences in correla-tions (greater correlations for compendium-coded estimates)were seen for women younger than 60 years and for women with12 or more years of education. Trend differences were seen forNative American women (p < .10).

Percentage Meeting PA Recommendations

Table 5 displays the percentage of participants meetingCDC–ACSM (≥ 30 min of moderate-intensity activities each ofthe 4 days), Surgeon General (≥ 150 kcal/d expended in at leastmoderate-intensity activities for each of the 4 days), and ACSMvigorous (≥ 20 min of vigorous-intensity activities, ≥ 2 of the 4days assessed) recommendations for PA, by sample strata. Per-centage of women meeting CDC–ACSM and Surgeon Generalrecommendations were higher when compendium-coded esti-mates were used. An 18% difference was found forCDC–ACSM recommendations and an 11% difference for Sur-geon General recommendations. However, more women wereclassified as meeting ACSM vigorous-intensity recommenda-tions when participant-coded estimates were used. A 22% dif-ference was found between compendium-coded and partici-pant-rated estimates. These same patterns were found for allsample strata, although the magnitude of the differences variedfrom group to group.

DISCUSSION

Overall Findings

At least two practical methods exist for estimating PA in-tensity. One method is to ask the respondent to rate the intensity


258

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of each activity reported, using terms light, moderate, or vigor-ous, with some instruction and examples for each term. Anothermethod is to use a uniform classification system, such as theCompendium of Physical Activities (1), to assign intensity lev-els to each activity reported. It is important to understand dis-crepancies between methods and whether these discrepancieshave meaningful implications for health and disease. Thus, thisstudy examined the agreement between these two methodsamong a triethnic sample of middle-aged women.

Our findings indicated that women reported more timespent in vigorous and light activities when they rated their inten-sity level, balanced by less time spent in moderate-intensity ac-tivities, relative to compendium estimates. The use of partici-pant-rated estimates yielded a smaller percentage of womenmeeting CDC–ACSM and Surgeon General recommendationsfor PA relative to compendium-coded estimates but a substan-tially higher percentage meeting ACSM vigorous recommenda-tions. Estimates of kilocalories per day based on compendiumcodes were more highly associated with pedometer step countsthan those based on participant ratings. Based on existingepidemiologic evidence (3), it is highly unlikely that 28% of

participants in our sample were meeting ACSM vigorous rec-ommendations, as would be suggested by participant ratings.Together, these findings suggest that the compendium worksquite well for assigning intensity to activities in ethnically di-verse women. The 1993 Compendium of Physical Activitieswas used to code activities in this study. An updated compen-dium was recently published (30). Although the updated com-pendium has added new activities and has modified MET levelsfor some activities, most changes have not resulted in majorchanges in classification of intensity (i.e., light, moderate, orvigorous). Thus, our results are unlikely to change substantiallyas a result of the new compendium.

Sample Subgroup Differences

Although cultural factors likely impact the experience andreporting of PA (5–9,12), our results were fairly consistent forwomen across ethnic, age, education, and body weight groups.This consistency suggests that the use of PA Records, whichcapture all daily activities, may reduce cultural bias that is oftenintroduced when researchers inquire about specific activities,many of which may not be culturally relevant, or do not inquire


TABLE 4Mean Energy Expenditure (With Standard Deviations) and Correlations Between Energy Expenditure and Pedometer Counts for

Participant-Rated Versus Compendium-Coded Estimates, by Ethnicity, Age, Education, and Obesity Status

Estimates of Daily Energy Expenditure (kcal/d)Correlations (r) Between kcal/d and

Pedometer Counts

Ppt-Rated Comp-Coded Difference t Ppt-Rated Comp-Coded t

Entire sample 2,706.7 2,953.7 –247.0 –12.7*** .17 .28 –2.0*(39.2) (36.5) (19.5)

EthnicityAfrican Americana 2,849.7 3,054.4 –204.7 –7.6*** .13 .22 –1.1

(59.3) (60.26) (26.85)Native Americanb 2,671.6 2,935.2 –263.5 –7.6*** .19 .36 –1.9

(64.4) (54.4) (34.6)Non-Hispanic Whitec 2,393.00 2,715.6 –322.6 –8.5*** .26 .34 –0.6

(63.62) (67.97) (38.1)Age

< 60 yearsd 2,764.6 3,029.9 –265.3 –11.1*** .16 .30 –2.23*(48.26) (43.6) (23.86)

≥ 60 yearse 2,569.1 2,772.6 –203.5 –6.1*** .11 .29 –1.6(64.4) (63.2) (33.3)

Education< 12 yearsf 2,731.4 2,980.7 –249.3 –3.8** .36 .05 1.3

(128.9) (133.8) (66.0)≥ 12 yearsg 2,704.3 2,951.1 –246.8 –12.1*** .17 .32 –2.6**

(41.2) (37.9) (20.4)Obesity

BMI < 30h 2,358.9 2,602.1 –243.2 –12.6*** .17 .19 –0.6(30.2) (28.6) (19.3)

BMI ≥ 30i 3,237.4 3,490.3 –252.8 –6.4*** –.09 –.02 –1.1(65.1) (55.4) (39.5)

Note. kcal/d = kilocalories per day; Ppt-rated = the use of participant-rated intensity (1.25 metabolic equivalents [METS] for light, 4 METS for moderate,and 7 METS for vigorous ratings) in the computation of kcal/d; comp-coded = the use of compendium-assigned MET values in the computation of kcals/d;BMI = body mass index.

an = 148. bn = 144. cn = 51. dn = 242. en = 101. fn = 30. gn = 313. hn = 208. in = 135.*p < .05. **p < .01. ***p < .001.

about activities that are more common in a particular culture.Agreement between methods for light and moderate activitiesand for CDC–ACSM and Surgeon General recommendationstended to be highest for African Americans. The higher agree-ment may be due, in part, to this population reporting less mod-erate and vigorous activities than other sample groups. Further,pedometer counts and estimated kilocalories per day, regardlessof method, were not associated in obese women. Heavierwomen expend more energy with the same amount of move-ment as leaner women, which may attenuate correlations be-tween movement (pedometer) and kilocalories in obese women.In addition, it is possible that excessive adipose tissue may limitthe reliability of motion sensors such as pedometers (31).

Women in the Cross-Cultural Activity Participation Study(CAPS) appeared to be more active than what is reported in na-tional surveys (3,4), particularly when compendium codes wereapplied. Data from the 1990 National Health Interview Surveyindicated that 26% of African American, 31% of non-HispanicWhite, 25% of overweight, and 21% of less educated womenmet CDC–ACSM recommendations (4). National surveys, how-ever, assess only exercise, sport, and leisure-time physical activ-ities. If we had considered only these activities in our study, therates meeting CDC–ACSM recommendations would have beencomparable to or perhaps even lower than rates reported in na-tional surveys. The use of PA Records, however, allowed us tocapture household and occupational activities that tend not to beassessed in traditional measures. Thus, our findings are consis-tent with those of others (32–34) who reported high rates of

moderate-intensity PA in ethnic minority women when exercise,leisure-time, occupational, and housework activities are consid-ered. They also emphasize the need for future studies to assessactivities that are common in the lives of women in general andwomen of Color in particular and to further examine how thesetypes of activities relate to health outcomes. For example,Weller and Corey found that the energy-expenditure-related re-duction in all-cause and cardiovascular disease mortality riskamong women over the age of 30 years was largely due to therole of nonleisure activities, such as household chores (35).Thus, future studies should focus on validating gender and eth-nically relevant PA measures (5,6) because the use of PA recordsin some study settings is often not feasible. In fact, a major goalof the CAPS projects was to create and validate an ethnicallyrelevant PA measure (36).

Clinical Significance of Findings

Our results suggest that when the goal of research is tobroadly classify participants who are meeting versus not meet-ing moderate-intensity recommendations for PA and health, ap-proximately 11% to 14% of participants will be classified differ-ently depending on whether participant ratings versuscompendium estimates of intensity are used. For some sub-groups, differential classification could be even higher. Whenthe goal of research is to broadly classify participants who aremeeting vigorous-intensity recommendations, 22% will be clas-sified differently depending on methods of assigning intensities.


TABLE 5The Percentage of Participants Meeting Recommendations for Physical Activity According to Participant-Rated Versus

Compendium-Coded Estimates, by Ethnicity, Age, Education, and Obesity Status

% Meeting CDC-ACSMRecommendations

% Meeting Surgeon GeneralRecommendations

% Meeting ACSMVigorous-IntensityRecommendations

Ppt-RatedComp-Coded χ2 Ppt-Rated

Comp-Coded χ2 or (p) Ppt-Rated

Comp-Coded χ2 or (p)

N 26.4 44.0 16.5*** 32.0 42.8 27.5*** 27.9 5.6 12.5***Ethnicity

African Americana 21.1 27.2 4.3* 25.9 26.5 4.4* 19.7 2.0 (.007)Native Americanb 30.1 56.6 6.0* 36.4 55.2 12.9*** 31.5 5.6 (.012)Non-Hispanic Whitec 31.4 56.9 3.1 37.3 54.9 7.1** 41.2 15.7 (1.0)

Age< 60 yearsd 26.7 44.6 11.3*** 32.5 44.2 23.7*** 29.2 5.8 (.000)≥ 60 yearse 25.7 42.6 5.1* 30.7 39.6 4.3* 24.8 5.0 (.329)

Education< 12 yearsf 26.7 53.3 0.4 23.3 43.3 (.660) 13.3 3.3 (1.0)≥ 12 yearsg 26.4 43.1 16.6*** 32.8 42.8 27.2*** 29.3 5.8 12.9***

ObesityBMI < 30h 28.2 49.0 8.8** 34.0 46.1 16.4*** 34.0 8.7 9.4**BMI ≥ 30i 23.7 63.3 7.2** 28.9 37.8 10.5*** 18.5 0.7 (1.0)

Note. Exact p values are reported when assumptions for a chi-square were violated, and a Fisher’s Exact Test was used. CDC–ACSM = Centers for DiseaseControl and Prevention–American College of Sports Medicine; Ppt-Rated = the use of participant-rated intensity; comp-coded = the use ofcompendium-assigned MET values; BMI = body mass index.

an = 148. bn = 144. cn = 51. dn = 242. en = 101. fn = 30. gn = 313. hn = 208. in = 135.*p < .05. **p < .01. ***p < .001.

We suspect that participants overestimated vigorous intensityand that participant ratings should not be used if vigorous inten-sity activities are the primary interest.

Daily increases of 70 to 215 kilocalories have been associ-ated with 14% to 36% reductions in mortality risk and have im-plications for changes in body weight (3). These estimates, how-ever, are based on structured physical activities and may notdirectly apply to unstructured, daily activities that were com-mon in our sample. Nonetheless, the 247 kcal/d difference be-tween estimates using compendium-coded and participant-ratedintensity are quite substantial. Thus, when the goal is to estimateenergy expenditure, the two methods produce meaningful dif-ferences. The purpose of the compendium is to have a consistentand standard approach to estimating activity intensity, and itmay be easier for participants and more time efficient to simplyhave participants report their activities and apply compendiumcodes. Further, the stronger correlations between estimates ofenergy expenditure (kcals) based on compendium-coded inten-sity levels and pedometer counts suggest that compendium esti-mates are more accurate, including in ethnically diverse women.

Study Limitations

There are several limitations to this study. As was statedthroughout, we cannot ascertain the “true” intensity levels of theparticipants’ activities. Heart rate monitors might have providedus with greater information to help in this classification. Partici-pants did wear pedometers, and compendium-coded estimateswere more strongly associated with pedometer counts than wereparticipant-rated estimates, but pedometers do not directly as-sess intensity. Instead, they provide estimates of summed move-ment, and they tend to be less accurate for very slow movements(37,38). In addition women could have overestimated or under-estimated duration of the actual activity coded. Biases in PA Re-cords relative to whole-room calorimetry were recently noted byBuchowski, Townsend, Chen, Acra, and Sun (14). Thus, in theabsence of a true criterion measure, the absolute degree of biasin measures is always unknown. Finally, although a majorstrength of this study is the inclusion of women from two under-studied ethnic groups—African Americans and Native Ameri-cans—these women tended to be more educated than womenfrom the communities in which they were drawn. However,rates of obesity among our African American and Native Ameri-can participants were similar to population estimates (28), andrates of PA were similar to those reported in other studies that in-cluded broader measures of PA (32–34). Our results may notgeneralize to other ethnically diverse women, particularly thosewith lower levels of education.

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Documents

Agreement between participant-rated and compendium-coded intensity of daily activities in a triethnic sample of women ages 40 years ears and older